Xuanwei and Fuyuan counties in China have the highest lung cancer rates in the world due to household air pollution from combustion of smoky coal for cooking and heating. To discover potential biomarkers of indoor combustion products, we profiled adducts at the Cys34 locus of human serum albumin (HSA) in 29 nonsmoking Xuanwei and Fuyuan females who used smoky coal, smokeless coal, or wood and 10 local controls who used electricity or gas fuel. Our untargeted adductomics method detected 50 tryptic peptides of HSA, containing Cys34 and prominent post-translational modifications. Putative adducts included Cys34 oxidation products, mixed disulfides, rearrangements, and truncations. The most significant differences in adduct levels across fuel types were observed for S-glutathione (S-GSH) and S-γ-glutamylcysteine (S-γ-GluCys), both of which were present at lower levels in subjects exposed to combustion products than in controls. After adjustment for age and personal measurements of airborne benzo(a)pyrene, the largest reductions in levels of S-GSH and S-γ-GluCys relative to controls were observed for users of smoky coal, compared to users of smokeless coal and wood. These results point to possible depletion of GSH, an essential antioxidant, and its precursor γ-GluCys in nonsmoking females exposed to indoor-combustion products in Xuanwei and Fuyuan, China.

Cancers are heterogeneous and genetically unstable. New methods are needed that provide the sensitivity and specificity to query single cells at the genetic loci that drive cancer progression, thereby enabling researchers to study the progression of individual tumors. Here, we report the development and application of a bead-based hemi-nested microfluidic droplet digital PCR (dPCR) technology to achieve 'quantitative' measurement and single-molecule sequencing of somatically acquired carcinogenic translocations at extremely low levels (<10(-6)) in healthy subjects. We use this technique in our healthy study population to determine the overall concentration of the t(14;18) translocation, which is strongly associated with follicular lymphoma. The nested dPCR approach improves the detection limit to 1×10(-7) or lower while maintaining the analysis efficiency and specificity. Further, the bead-based dPCR enabled us to isolate and quantify the relative amounts of the various clonal forms of t(14;18) translocation in these subjects, and the single-molecule sensitivity and resolution of dPCR led to the discovery of new clonal forms of t(14;18) that were otherwise masked by the conventional quantitative PCR measurements. In this manner, we created a quantitative map for this carcinogenic mutation in this healthy population and identified the positions on chromosomes 14 and 18 where the vast majority of these t(14;18) events occur.

Background

Recent evidence has shown that humans metabolize benzene more efficiently at environmental air concentrations than at concentrations > 1 ppm. This led us to speculate that an unidentified metabolic pathway was mainly responsible for benzene metabolism at ambient levels.

Objective

We statistically tested whether human metabolism of benzene is better fitted by a kinetic model having two pathways rather than one.

Methods

We fit Michaelis-Menten-like models to levels of urinary benzene metabolites and the corresponding air concentrations for 263 nonsmoking Chinese females. Estimated benzene concentrations ranged from less than 0.001 ppm to 299 ppm, with 10th and 90th percentile values of 0.002 ppm and 8.97 ppm, respectively.

Results

Using values of Akaike's information criterion obtained under the two models, we found strong statistical evidence favoring two metabolic pathways, with respective affinities (benzene air concentrations analogous to K(m) values) of 301 ppm for the low-affinity pathway (probably dominated by cytochrome P450 enzyme 2E1) and 0.594 ppm for the high-affinity pathway (unknown). The exposure-specific metabolite level predicted by our two-pathway model at nonsaturating concentrations was 184 muM/ppm of benzene, a value close to an independent estimate of 194 muM/ppm for a typical nonsmoking Chinese female. Our results indicate that a nonsmoking woman would metabolize about three times more benzene from the ambient environment under the two-pathway model (184 muM/ppm) than under the one-pathway model (68.6 muM/ppm). In fact, 73% of the ambient benzene dose would be metabolized via the unidentified high-affinity pathway.

Conclusion

Because regulatory risk assessments have assumed nonsaturating metabolism of benzene in persons exposed to air concentrations well above 10 ppm, our findings suggest that the true leukemia risks could be substantially greater than currently thought at ambient levels of exposure-about 3-fold higher among nonsmoking females in the general population.

The mechanism of toxicity of the leukemogen benzene is not entirely known. This pilot study used RNA-sequencing (RNA-seq) technology to examine the effect of benzene exposure on gene expression in peripheral blood mononuclear cells obtained from 10 workers occupationally exposed to high levels of benzene (≥5 ppm) in air and 10 matched unexposed control workers, from a large study (n = 125) in which gene expression was previously measured by microarray. RNA-seq is more sensitive and has a wider dynamic range for the quantification of gene expression. Further, it has the ability to detect novel transcripts and alternative splice variants. The main conclusions from our analysis of the 20 workers by RNA-seq are as follows: The Pearson correlation between the two technical replicates for the RNA-seq experiments was 0.98 and the correlation between RNA-seq and microarray signals for the 20 subjects was around 0.6. 60% of the transcripts with detected reads from the RNA-seq experiments did not have corresponding probes on the microarrays. Fifty-three percent of the transcripts detected by RNA-seq and 99% of those with probes on the microarray were protein-coding. There was a significant overlap (P < 0.05) in transcripts declared differentially expressed due to benzene exposure using the two technologies. About 20% of the transcripts declared differentially expressed using the RNA-seq data were non-coding transcripts. Six transcripts were determined (false-discovery rate < 0.05) to be alternatively spliced as a result of benzene exposure. Overall, this pilot study shows that RNA-seq can complement the information obtained by microarray in the analysis of changes in transcript expression from chemical exposures.

Lung cancer in never smokers, which has been partially attributed to household solid fuel use (i.e., coal), is etiologically and clinically different from lung cancer attributed to tobacco smoking. To explore the spectrum of driver mutations among lung cancer tissues from never smokers, specifically in a population where high lung cancer rates have been attributed to indoor air pollution from domestic coal use, multiplexed assays were used to detect >40 point mutations, insertions, and deletions (EGFR, KRAS, BRAF, HER2, NRAS, PIK3CA, MEK1, AKT1, and PTEN) among the lung tumors of confirmed never smoking females from Xuanwei, China [32 adenocarcinomas (ADCs), 7 squamous cell carcinomas (SCCs), 1 adenosquamous carcinoma (ADSC)]. EGFR mutations were detected in 35% of tumors. 46% of these involved EGFR exon 18 G719X, while 14% were exon 21 L858R mutations. KRAS mutations, all of which were G12C_34G>T, were observed in 15% of tumors. EGFR and KRAS mutations were mutually exclusive, and no mutations were observed in the other tested genes. Most point mutations were transversions and were also found in tumors from patients who used coal in their homes. Our high mutation frequencies in EGFR exon 18 and KRAS and low mutation frequency in EGFR exon 21 are strikingly divergent from those in other smoking and never smoking populations from Asia. Given that our subjects live in a region where coal is typically burned indoors, our findings provide new insights into the pathogenesis of lung cancer among never smoking females exposed to indoor air pollution from coal.

Fluorescence in situ hybridization (FISH) is a powerful new technique that allows numerical chromosome aberrations (aneuploidy) to be detected in interphase cells. In previous studies, FISH has been used to demonstrate that the benzene metabolites hydroquinone and 1,2,4-benzenetriol induce aneuploidy of chromosomes 7 and 9 in cultures of human cells. In the present study, we used an interphase FISH procedure to perform cytogenetic analyses on the blood cells of 43 workers exposed to benzene (median = 31 ppm, 8-hr time-weighted average) and 44 matched controls from Shanghai, China. High benzene exposure (> 31 ppm, n = 22) increased the hyperdiploid frequency of chromosome 9 (p < 0.01), but lower exposure (< or = 31 ppm, n = 21) did not. Trisomy 9 was the major form of benzene-induced hyperdiploidy. The level of hyperploidy in exposed workers correlated with their urinary phenol level (r = 0.58, p < 0.0001), a measure of internal benzene dose. A significant correlation was also found between hyperdiploidy and decreased absolute lymphocyte count, an indicator of benzene hematotoxicity, in the exposed group (r = -0.44, p = 0.003) but not in controls (r = -0.09, p = 0.58). These results show that high benzene exposure induces aneuploidy of chromosome 9 in nondiseased individuals, with trisomy being the most prevalent form. They further highlight the usefulness of interphase cytogenetics and FISH for the rapid and sensitive detection of aneuploidy in exposed human populations.

Sufficient evidence supports a relationship between certain myeloid neoplasms and exposure to benzene or formaldehyde. DNA methylation could underlie benzene- and formaldehyde-induced health outcomes, but data in exposed human populations are limited. We conducted two cross-sectional epigenome-wide association studies (EWAS), one in workers exposed to benzene and another in workers exposed to formaldehyde. Using HumanMethylation450 BeadChips, we investigated differences in blood cell DNA methylation among 50 benzene-exposed subjects and 48 controls, and among 31 formaldehyde-exposed subjects and 40 controls. We performed CpG-level and regional-level analyses. In the benzene EWAS, we found genome-wide significant alterations, i.e., FWER-controlled P-values <0.05, in the mean and variance of methylation at 22 and 318 CpG sites, respectively, and in mean methylation of a large genomic region. Pathway analysis of genes corresponding to benzene-associated differential methylation sites revealed an impact on the AMPK signalling pathway. In formaldehyde-exposed subjects compared to controls, 9 CpGs in the DUSP22 gene promoter had genome-wide significant decreased methylation variability and a large region of the HOXA5 promoter with 44 CpGs was hypomethylated. Our findings suggest that DNA methylation may contribute to the pathogenesis of diseases related to benzene and formaldehyde exposure. Aberrant expression and methylation of HOXA5 previously has been shown to be clinically significant in myeloid leukaemias. The tumour suppressor gene DUSP22 is a potential biomarker of exposure to formaldehyde, and irregularities have been associated with multiple exposures and diseases.

Background

Much of the heritable risk of renal cell carcinoma (RCC) associated with common genetic variation is unexplained. New analytic approaches have been developed to increase the discovery of risk variants in genome-wide association studies (GWAS), including multi-locus testing through pathway analysis.

Methods

We conducted a pathway analysis using GWAS summary data from six previous scans (10,784 cases and 20,406 controls) and evaluated 3,678 pathways and gene sets drawn from the Molecular Signatures Database. To replicate findings, we analyzed GWAS summary data from the UK Biobank (903 cases and 451,361 controls) and the Genetic Epidemiology Research on Adult Health and Aging cohort (317 cases and 50,511 controls).

Results

We identified 14 pathways/gene sets associated with RCC in both the discovery (P < 1.36 × 10^-5, the Bonferroni correction threshold) and replication (P < 0.05) sets, 10 of which include components of the PI3K/AKT pathway. In tests across 2,035 genes in these pathways, associations (Bonferroni corrected P < 2.46 × 10^-5 in discovery and replication sets combined) were observed for CASP9, TIPIN, and CDKN2C. The strongest SNP signal was for rs12124078 (P _Discovery = 2.6 × 10^-5; P _Replication = 1.5 × 10^-4; P _Combined = 6.9 × 10^-8), a CASP9 expression quantitative trait locus.

Conclusions

Our pathway analysis implicates genetic variation within the PI3K/AKT pathway as a source of RCC heritability and identifies several promising novel susceptibility genes, including CASP9, which warrant further investigation.

Impact

Our findings illustrate the value of pathway analysis as a complementary approach to analyzing GWAS data.

Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from <1 ppm to >10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and CYP2E1. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings.

Background

Metabolism of benzene produces reactive electrophiles, including benzene oxide (BO), 1,4-benzoquinone (1,4-BQ), and 1,2-benzoquinone (1,2-BQ), that are capable of reacting with blood proteins to produce adducts.

Objectives

The main purpose of this study was to characterize relationships between levels of albumin adducts of these electrophiles in blood and the corresponding benzene exposures in benzene-exposed and control workers, after adjusting for important covariates. Because second blood samples were obtained from a subset of exposed workers, we also desired to estimate within-person and between-person variance components for the three adducts.

Methods

We measured albumin adducts and benzene exposures in 250 benzene-exposed workers (exposure range, 0.26-54.5 ppm) and 140 control workers (exposure range < 0.01-0.53 ppm) from Tianjin, China. Separate multiple linear regression models were fitted to the logged adduct levels for workers exposed to benzene < 1 ppm and > or =1 ppm. Mixed-effects models were used to estimate within-person and between-person variance components of adduct levels.

Results

We observed nonlinear (hockey-stick shaped) exposure-adduct relationships in log-scale, with inflection points between about 0.5 and 5 ppm. These inflection points represent air concentrations at which benzene contributed marginally to background adducts derived from smoking and from dietary and endogenous sources. Adduct levels were significantly affected by the blood-collection medium (serum or plasma containing either heparin or EDTA), smoking, age, and body mass index. When model predictions of adduct levels were plotted versus benzene exposure > or =1 ppm, we observed marked downward concavity, particularly for adducts of the benzoquinones. The between-person variance component of adduct levels increased in the order 1,2-BQ < 1,4-BQ < BO, whereas the within-person variance components of the three adducts followed the reverse order.

Conclusions

Although albumin adducts of BO and the benzoquinones reflect exposures to benzene > or = 1 ppm, they would not be useful biomarkers of exposure at ambient levels of benzene, which tend to be < 0.01 ppm, or in those working populations where exposures are consistently < 1 ppm. The concavity of exposure-adduct relationships is consistent with saturable metabolism of benzene at air concentrations > 1 ppm. The surprisingly large effect of the blood-collection medium on adduct levels, particularly those of the benzoquinones, should be further investigated.